Package: LPGraph 2.1
Kaijun Wang
LPGraph: Nonparametric Smoothing of Laplacian Graph Spectra
A nonparametric method to approximate Laplacian graph spectra of a network with ordered vertices. This provides a computationally efficient algorithm for obtaining an accurate and smooth estimate of the graph Laplacian basis. The approximation results can then be used for tasks like change point detection, k-sample testing, and so on. The primary reference is Mukhopadhyay, S. and Wang, K. (2018, Technical Report).
Authors:
LPGraph_2.1.tar.gz
LPGraph_2.1.tar.gz(r-4.5-noble)LPGraph_2.1.tar.gz(r-4.4-noble)
LPGraph_2.1.tgz(r-4.4-emscripten)LPGraph_2.1.tgz(r-4.3-emscripten)
LPGraph.pdf |LPGraph.html✨
LPGraph/json (API)
# Install 'LPGraph' in R: |
install.packages('LPGraph', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- senate - Senate Vote Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:4eb555270d. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 17 2024 |
R-4.5-linux | OK | Nov 17 2024 |
Exports:LaplacianLP.basisLP.struct.testLPSpectralwt.mean
Dependencies:abindbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyrfansifarverFormulagenericsggplot2gluegtableisobandlabelinglatticelifecyclelme4magrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigPMApurrrquantregR6RColorBrewerRcppRcppEigenrlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Nonparametric Smoothing of Laplacian Graph Spectra | LPGraph-package LPGraph |
Computes LP basis function of a discrete distribution | LP.basis wt.mean |
Detection of structures in an ordered-network. | Laplacian LP.struct.test |
Nonparametric smooth approximation of the Laplacian graph spectra | LPSpectral |
Senate Vote Data | senate |